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The case for a smarter oil and gas industry
White Paper Oil and Gas Industry
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The oil and gas industry is, in one sense, a very simple
business: Its about extracting large amounts o a small number
o substances rom the earth or use by consumers. But this
conceptually straightorward task is risky, dangerous, wildly
expensive and very, very important to everyone on the planet.
Its also an intricately related system o systems, ranging
rom the relentless geologic search operations, to the awesome
engineering needed to capture resources miles beneath
the ocean oor, to a supply chain o giant physical assets
(pipelines, tankers, storage acilities and refneries). Along the
way, irrevocable decisions must be made about converting a
resource into one end product or another in anticipation o
uture patterns in weather, trafc or consumer buying behavior,and only then delivering raw materials to other industries and
retail products to outlets everywhere.
Some o the largest companies in the world compete in
this industry. It is an industry where fnancial commitments
must be made years ahead o payback, putting a tremendous
premium on predictive inormation that can be trusted.
And the fnancial uncertainty is compounded by political
uncertainty, with governments regulating its activities in
many dimensions, as well as actively participating in the
industry itsel.
It is an industry where prices uctuate based not only on
supply and demand, but on economic orecasts, currency
trends and speculation. It has a results-oriented, show me
engineering culture, a lot o fnancial sophistication in
the C-suite, a need or collaboration between frms on major
projects and a sub-industry o support, service and construction
frms that can mask the true points o decision-making on
major eorts.
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As the events of April 20, 2010 have shown, the
cost of a single accident can be devastating. The
spill in the Gulf of Mexico will influence how the
industry moves forward in ways that are not yetknownalthough a tougher regulatory and
compliance environment is a certainty.
On top o that, its an industry where, as the events o
April 20, 2010 have shown, the cost o a single accident can
be devastating fnancially, environmentally and in the loss
o lie. The gul spill will inuence how the industry moves
orward in a number ways that are yet to be known though
a tougher regulatory and compliance environment is a
certainty.
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technologies as horizontal drilling and multilateral wells.
But in general, the readings and measurements are notshared across tools or processes, and are highly dependent
on human interpretation, making it difcult to optimize in
an integrated and timely way.
The same goes or business intelligence. The analytic tools
in the industry today are oten very sophisticated scientifc
devices. But most are ocused on answering a particular
question, such as: Is there oil down there? or How long
can we expect that saety device to keep working? Those
dont scratch the surace o what is possible by mining
captured data in real time, in an interconnected way, with
new analytical tools.
What catalysts will drive the oil and gas
industry to become smarter?Given the difculty o fnding new reserves, combined with
rising conservation and environmental pressures, we might
have expected to see more o a transormation in this industry
already. But sustained higher prices and rising demand in
emerging economies, along with the growing importance o
Liquefed Natural Gas (LNG) and Shale Gas, have combined
to give the industry something o a second wind. Regardless
o how ast renewable energy sources are developed, its widelyagreed that the demand or marketed energy will continue to
grow into the oreseeable uture, by as much as 50 percent
rom current levels. So what will fnally convince the industry
that it needs to become smarter?
Oil and Gas Industry
The industry also fnds itsel in the crosshairs o the great
global awakening about the environment, and acing anear-universal desire to see some o its main products
completely replaced with renewable alternatives. All in all,
a lot to deal with.
Considering the fnancial risks, as well as the growing
difculty o locating new reserves, its no surprise that oil
and gas frms have been signifcant users o inormation
technology or a long time, both upstream (exploration
and production) and downstream (refning and delivery).
This includes analog instrumentation on wells up to 75 years
old. More recent systems capture data digitally, but with a
wide variety o tools and processes that reects 40 years o
experimentation and customization. And these instruments
are operated by a specialized workorce with a well-developed
(and thus perishable, when they retire) body o tacit
knowledge.
Thus, the oil and gas industry already has a level o
instrumentation that probably exceeds that o most other
industries, a level that will only grow in the years ahead,
especially upstream, as new energy targets become increasingly
remote. This instrumentation enables such leading-edge
Regardless of how fast renewable energy sources
are developed, its widely agreed that the demand
for marketed energy will continue to grow by as
much as 50 percent from current levels.
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Dwindling productivity
A decade ago, there was a burst o mega-mergers aimed atsignifcant productivity gains. That strategy paid o, but has
now about run its course. Recently announced layos by a
major international oil company and the shopping o their
downstream capabilities both underscore that many frms
are scrutinizing their operations very careully or urther
improvements. But the well is nearly dry in trying to
squeeze additional margin out o current ways o doing
business. The cost o liting oil out o the earth keeps
rising in the U.S. by as much as 18 percent over what it
was as recently as 2006. As an industry that gets a lot o
attention rom the investment community, oil and gas frms
will have a powerul incentive to achieve undamental
changes in how work is done within the industry i they
hope to take their fnancial perormance to the next level.
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The cost of lifting oil out of the earth keeps
rising - in the U.S. by as much as 18 percent over
what it was as recently as 2006.
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The natural environmentEnvironmental pressures will escalate rom both public
and private sources, placing even more o a premium on
developing processes and operations that leverage system
intelligence to meet and maintain a frms environmental
objectives. As the world demonstrates an increasing level
o concern about all orms o emissions, the ability to know,
evaluate and respond to emissions data, in real time, will
represent a signifcant competitive advantage. So will the
ability to quickly recognize, understand and fx breakdowns
o any sort throughout the system.
Our approach to smarter oil and gasThe industry is no stranger to doing original research in
basic science, and many frms maintain signifcant laboratories.
Some also support think tanks to explore the impact o
various issues and public policies. And, as weve seen, its
an industry with a lot a highly instrumented, heavy duty
inrastructure that is operated by highly trained personnel.
So in what sense is the oil and gas industry not smart
enough already?
The answer to that question lies in the very breadth and
complexity o the industry itsel the amount oinstrumentation in use today, the amount o data already
being captured, and the vast gains to be had rom insights
and actions that data could provide i it were integrated
and analyzed in real time across the industrys vast global
landscape, where even small improvements can add up to
multi-billion dollar payos.
When we think about where the industry can start becoming
smarter, three key areas jump out.
Oil and Gas Industry
The need for better visibilityAs the odds o fnding new sources become longer, and
optimizing the downstream more essential, the fnancial
leadership at major frms will demand more line o sight into
the fnancial impact o operating decisions. But that wont be
possible without creating a more integrated, transparent and
predictive analytic capability. The oil and gas industry is also
notable or the degree to which key operating decisions are
oten made in real time by individuals with hands-on process
responsibility, rather than hierarchical authority. This can be
especially true when responsibilities are shared among
corporations acting in consortium. So pressure or better
visibility on key perormance metrics will come rom engineersat the process level, as well as rom the corporate boardroom.
Due diligence
As frms collaborate to und expensive explorations and
jointly fnanced inrastructures, there will be a heightened
premium on being a more knowledgeable dealmaker. Trust
is never in oversupply in an industry that regularly makes
multi-billion dollar trades o invisible assets. So being a
successul player in this environment will depend more
than ever on knowing in real time ones own circumstances
(assets, fnances, markets, skills, commitments), AND being
able to accurately evaluate inormation oered by others.
The stakes will be too great to play industry poker with
twentieth-century levels o knowledge.
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Its been estimated that some industry workers spend upto 60 percent o their time mining data. Yet even with all
that brain power siting through numbers and images or
patterns, the average recovery rom a given feld is, according
to several surveys, around 30 percent. Other studies, however,
have reported that recovery can go as high as 70 percent
with the help o secondary recovery techniques, driven by
the data. So the fnancial reward or increasing the amount
o resource extracted per reservoir would be, on an industry-
wide basis, gigantic.
And it will not only be more proftable, but saer too, or
both workers and the environment. By using historicaltrends linked to event triggers, the industry will be able to
create a sense-and-respond environment that maximizes
well lie and minimizes physical risks, anticipating situations
remotely and responding automatically. Where tacit knowledge
is vital, frms will bring together global teams (including
retirees employed on a part-time basis) to analyze sensitive
data in secure real-time virtual collaboration. The payo:
longer well lie, optimized production, and less risk to people
and the environment.
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Enhanced exploration and productionThe harder it becomes to fnd oil and gas reserves, the more it
makes sense to look or them with instrumentation, analytics
and graphic representation. By integrating seismic and
geologic data rom multiple sources, and using advanced data
modeling combined with supercomputing (including seismic
cloud computing or above-petascale resources), the industry
can fnd reservoirs that are very remote, like the large Tupi
feld that is 180 miles o the coast o Brazil, beneath 7000 eet
o water, 10,000 eet o sand and rock, and 6600 eet o salt.
When it comes to getting the most out o reservoirs that have
already been identifed, a host o new, enhanced oil recoverytechniques have been developed. But each one adds more
physical variables to manage, and more volumes to estimate
and track. By using advanced visualization to render larger
amounts o complex data in more intuitive ways, a smarter
industry can achieve improved decision making and aster
time-to-oil. And by deploying advanced nano-sensors to
improve reservoir modeling, as well as drawing on spatial and
temporal data assimilation rom time-lapse seismic systems,
it can run predictive assumptions that dramatically increase
efciency in extracting oil and gas.
Using integrated seismic and geologic data, advanced data modeling and supercomputing, its possible
to find remote reservoirs such as the Tupi field located 180 miles off the coast of Brazil under 7000 feet
of water, 10,000 feet of sand and rock and 6600 feet of salt.
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8 Oil and Gas Industry
Its already starting to happen. A major oil company iscurrently working to extend oil feld lie and increase
production yield through the implementation o new
decision support tools. They expect to reduce unplanned
downtime by 5 percent, as well as to reduce costs by up to
30 percent through the use o predictive maintenance
techniques. These decision-support tools bridge the gap
between dierent parts o the companys operations so that
BOTH data and employee knowledge can be leveraged across
all processes, resulting in lower costs and improved production
efciency, as well as great interdisciplinary collaboration.
Much o the industrys uture is being invented in thelaboratory right now. For example, IBM Research is
doing original research in reservoir simulation, grid-based
visualization, 4D seismic imaging, and stream analytics.
And academic institutions are working on it too, such as
the University o Calgary, which is teaming with the IBM
Center o Excellence there to ocus on oil sands development.
Stanord University is also leading a multidisciplinary,
multi-department consortium to conduct research in such
areas as optimizing where and when to drill, the design o
wells to be drilled and the type o monitoring that would
maximize the lie o the well.
As oil and gas become harder and harder to fnd, the tools
to look or them in ever smarter ways will only grow.
Improved asset managementThe industry is both asset and data intensive. An oil well
at sea can easily cost $150 million. And such a well can
generate a terabyte o data per day, roughly the inormation
in 1 million medium-sized novels. But ew frms currently
manage their assets in a way that optimizes the data they
are already gathering.
Consider, or example, how a typical oil and gas frm manages
alarms. To ensure saety and prevent environmental dangers,
the industry careully monitors its systems or unusual events.
When an alarm goes o, the technician who receives the
alarm will ascertain what has gone wrong and decide how torespond. Certainly it would be helpul or them to be able to
consult the systems history (to see i this event has happened
beore), or its maintenance inormation (to see what work has
been done on this system, or what maintenance is being done
close by, which might have caused the event), or its purchase
records or the ailing part (to see i the right part had been
installed in the frst place), etc. Today, all o these elements o
data are likely to reside in dierent places, perhaps even
dierent and incompatible systems. And even i all o this
inormation were instantly available to the operator, he would
still need to perorm the act o integrating the data into a
response plan, because very little analytic intelligence has
been applied to the data other than what can be provided by
the operator himsel.
An oil well at sea can easily cost $150 million.
And such a well can generate a terabyte of data
per day, roughly the information in 1 million
medium-sized novels.
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This challenge has attracted serious academic investigation.For example, the Norwegian University o Science and
Technology is working to build a multidisciplinary approach
to the integration o asset management processes.
As science-fction writer William Gibson once said, the uture
is already here, just not evenly distributed. But that uture
has already arrived at a major global energy company that is
using a design once-build many approach or its oshore
production acilities, enabling them to bring new felds to
production in a raction o the time and cost o previous
operations. Consider what design once-build many can
mean in a sphere o human activity where a structure thatis routinely customized design once-build once can
cost $150 million.
Optimize global operations
Few industries are as inherently global as oil and gas.
But the challenge o turning an oil and gas company into
a truly global enterprise remains daunting. One o the
key challenges is the handovers that exist throughout
the industry across proessional, geographic, national and
chronological boundaries. How does a company ensure
that they are seamless and eliminating the redundancies
while maintaining knowledge through the lie o systems
and assets?
Few industries are as inherently global as oil
and gas.
But i the data had been integrated, in context somethingthat a smarter asset management system can do it would
not only add speed and accuracy, but also automate and
apply analytics to the alarm itsel, leveraging the wisdom o
the companys prior experience. In other words, it would
be smarter.
That is just one example, and a hypothetical one at that.
But it gives a sense or how much smarter asset management
in the oil and gas industry can become when it applies
instrumentation and analytics in an interconnected and
integrated way. By combining workow inormation and
decision support tools across production activities, the industrywill be able to use dashboards to optimize both planned and
unplanned shutdowns, assess the preparedness o turnarounds,
run scenario planning with the beneft o mathematical models,
asset by asset, and thus maximize production, while minimizing
cost, down time and human error.
For the frst time, engineering, operations and maintenance
unctions will be able to collaborate through knowledge
sharing tools and peer networks that acilitate the sharing o
tacit knowledge, especially regarding saety and reliability
issues. And we will even be able to automatically actor
marketplace uctuations in supply and demand into decisions
about production.
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Currently, a major liquefed petroleum corporation is workingto implement a comprehensive radio-requency identifcation
(RFID)-enabled solution or tracking its cylinders. Like
everyone else, they need greater efciency, but they also need
to prevent thet. Their RFID-tag solution will address both o
those needs, tracking the consumption level at each distributor,
while identiying unusual consumption patterns and short
turnaround times, indicating diversion. The customer
dashboard they are creating to oversee all o this will enable
the company to gain new and actionable business insights in
every step o their operation rom bottling plant to cylinder
management. Thats what we mean by smart.
Globalized solutions will require the industry to make the
most o new compute-intensive analytics. Thats why King
Abdullah University o Science and Technology is working
to build the most complex high perormance computing
system in the Middle East. And IBMs Center o Excellence
in Stavanger, Norway is ocusing on the science o Integrated
Operations rom the perspective o the industrys unique
global needs. Collaboration will be key, as oil and gas frms,
IT vendors, strategic business partners and academics work
together with oil and gas standards bodies in collaboratories
to drive more smartness into the industry.
In a smarter industry, handovers will capture real-timefeld, plant, pipeline and logistics inormation or improved
visibility, planning, exibility and decision support through
sensor-based technologies deployed enterprise-wide. And
that will automate supply chain transactions implemented
through advanced analytics and optimization programs.
Supply chains will be standardized and integrated across
multiple geographies through a common open standards-
based inormation inrastructure.
Already, one oil company is able to simultaneously monitor
the ow o oil rom more than 100 felds and nearly 50 gas-oil
separators, through 11,000 miles o pipeline, into sevenrefneries and chemical plants with only two dozen people
in one remote location.
Building on that example, a smarter industry will consolidate
global support operations into centers o excellence that use
remote collaboration and robust knowledge management
capabilities. It will also reduce IT costs and energy use through
standardized tracking and consolidation. Predictive weather
models, which are getting better all the time, will be harnessed
to minimize storm-related damages and supply disruptions.
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ConclusionThe oil and gas industry has never been an easy business,
and its not getting any easier. Virtually no one expects the
industry to survive the twenty-frst century in its present
orm, with its present products. Yet its importance in
todays economy cannot be overestimated, and will remain
enormous or a long time, matched only by the size o the
sel-reinvention it must execute, as it gradually transorms
rom Oil and Gas to Energy.
In this environment, there is no alternative but or the
industry to become much smarter. The degree to which
it can do that will depend on the vision o its leaders, aswell as on the ability o its business partners, including
IBM and many other vendors, to apply instrumentation,
interconnectedness and advanced intelligence to the awesome
physical and fnancial challenges o this unique industry.
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